1 Introducing Cognitive Neuroscience: Concepts and History
1.1 What is cognitive neuroscience
Very early on in our lives, we become aware of the world around us and also of inner thoughts and feelings, which together build our sense of ourselves as sentient organisms separate from the environment. Our conscious mind feels different from the physical world that surrounds us. During childhood, it is not uncommon to wonder how is it possible that a conscious intention to, for example, move our hand instantly triggers such a movement. How does my mind affect my body? And conversely, how does the body affect the mind? Humans have wondered about the nature of the mind, of the physical body and of their relationship since the dawn of our species. Although nowadays we are far from having comprehensive scientific explanations to these questions, hundreds of years of investigation have brought impressive discoveries and scientific advances, and many of these have laid the path to the field of Cognitive Neuroscience. In the same manner as our knowledge of how the mind and the brain work has been growing and improving over the centuries, theories and evidence in Cognitive Neuroscience are constantly being tested and refined, as it happens in any scientific discipline. This is reflected on the definitions or description of its object of study.
Initially, the goal of Cognitive Neuroscience was set as the localization of cognitive processes in the brain. Using non-invasive neuroimaging techniques in humans, and also data from neuropsychological patients and disruption/stimulation devices, or invasive neuronal recordings and disruption/stimulation in non-human animals, Cognitive Neuroscience aims to localize which parts of the brain underlie processes described by Cognitive Psychology, such as Perception, Memory, Attention, or Emotion, among many others.
This definition, however, relies on two assumptions that are highly contended. First, the extent to which cognition in the brain is organized in a clearly localized manner is a matter of intense and, sometimes, polarized debate. As we will see in coming sections, there is no scientific basis to the notion that a single brain area is devoted to a unique cognitive process (e.g. occipital cortex to visual perception, frontal lobes to executive processes). Also, brains are highly complex and dynamic organs: neurons of different types are arranged in groups or coalitions, which cluster in brain areas and subcortical nuclei that in turn organize into networks of connected areas. Hence, the level of neural organization at which processes should be localized is unclear. Does e.g. perception correspond to the activity of single neurons, of coalitions of them, to regions within the occipital lobe, to the whole occipital lobe, or to this in connection with temporal and frontal lobes? Second in contention, the extent to which the current existing repertoire and understanding of psychological processes (e.g. Perception, Attention, Language…) is accurate is also a matter of debate. It should be taken into account that cognitive processes are hypothetical constructs that have been employed in Cognitive Psychology to explain the human mind; however, these are only working models and thus they could be partially mistaken. In this sense, current evidence does not support the notion of a strong equivalence between one brain region and one cognitive process. As an example, the occipital cortex is involved in visual perception, but this lobe is also recruited during imagination, learning, memory, attention, and even when blind individuals read Braille. Conversely, visual perception recruits regions of the occipital, temporal, parietal and frontal cortices. Taking all this into account, we should be wary of simplistic statements that localize mental functions in specific brain areas. The occipital lobe is involved in visual perception, yes, but the sole function of the occipital lobe is not perception, and explaining perception does not mean locating it solely on the occipital lobe. Drawing on a familiar assertion, that there is a fear center in our brain and that it is localized in the amygdala is an inaccurate statement. A more accurate assertion would be that the amygdala is involved in many mental functions, that include fear processing but also other categories of emotions, reward processing, learning and selection of relevant information, among others.
A more comprehensive definition of Cognitive Neuroscience would be that it is multidisciplinary scientific field that aims to explain how the brain supports cognition. Researchers in the field aim to provide physiological or mechanistic descriptions of how neural activity at different scales, being these isolated neurons, their coalition, brain regions and/or networks, give rise to (human) mental functions. Hence, rather than merely describing or linking specific brain regions with cognitive processes, an ulterior goal of the discipline is explaining how this happens, in mechanistic or algorithmic terms. Essential to this is the study of how neurons in different parts of the brain code or represent information, and how this information is transferred between different regions, that is, how communication among brain areas takes place in an effective manner.
A scientific field that aims to bridge between two domains of such complexity such as the human brain and mind cannot rely on a single discipline, and because of this Cognitive Neuroscience is a multidisciplinary endeavor. Relevant fields include Psychology, Neuroscience, Biomedical and Signal Engineering, Philosophy of Mind and Physics, among others. The variety of sources of knowledge that along history have led to our discipline is a precursor of this.
1.2 Historical background
1.2.1 The mind-body problem
The intuition that the mind and body correspond to qualitatively different types of substances has accompanied humans for a long time. Attempts to explain our subjective mental experience, or qualia (e.g. the redness of the color red) as based on a physical substance (the body) are often rejected as implausible, given the belief that the mind (or spiritual soul) pertains to a reality that cannot be reduced to physical entities (such as the body). Still nowadays philosophers such as David Chalmers contend that whereas science will be able to eventually explain how the human brain performs mental mechanical functions, explaining why and how humans have qualia is the “hard problem” of consciousness. Many believe science will never be able to answer this question.
René Descartes (17th century) is the philosopher that best represents the mind-body Dualism, which claims that mind and body are composed by qualitatively different substances. Although the res extensa (matter) and res cogitans (mental substance) have different properties or qualities according to Descartes, they interact causally through the pineal gland in the brain. Dualism is still part of some current philosophical traditions and it is also embraced by several religions, but its relevance for a scientific discipline such as Cognitive Neuroscience is severely limited. Given the core assumption of Cartesian dualism that the mind pertains to a reality that is qualitatively different from the body, how could we explain and understand the mind by manipulating and measuring the body? Science relies on manipulation and measurement to understand its object of investigation, and philosophical approaches that locate the mind and body in the same reality are much better suited to study them.
In this line, Monism contends that mind and body are not distinct realities, but rather correspond to the same substance. A subtype of this current is the Dual-Aspect theory by Baruch Spinoza (17th century), where mind and brain are two different levels of explanation of the same unique phenomenon, which corresponds to the same reality (according to Spinoza, this reality was God). That is, the same phenomenon can be explained or understood in two different ways. This approach is usually presented in analogy with explanations of the physics of light, which can be explained as a wave or as particles (photons). Also in the 17th century, Margaret Cavendish, Duchess of Newcastle, argued against dualism by claiming:
Sensitive and rational matter […] makes not only the brain but all thoughts, conceptions, imaginations […] and whatsoever motions are in the head or brain.
An additional philosophical approach that pertains to the goals of Cognitive Neuroscience is Eliminative materialism, or Reductionism, pioneered by the philosopher Patricia Churchland (XXI). This perspective contends that although currently we need psychological or mental descriptions of phenomena, eventually these will be eliminated and replaced by purely biological concepts once we acquire enough mature knowledge of brain function. Although this perspective has been criticized as radical and there are many who think that psychological concepts are essential to explain the biology of cognition, reductionists often refer to other fields of science, where initial explanative concepts were later eliminated as explanations improved (e.g. Phlogiston theory).
1.2.2 Heart or brain?
Setting philosophical perspectives about the mind-body problem aside, a different but revealing note on our history is where in the body ancient thinkers located the human mind. Although nowadays it is accepted as obvious that the brain is the site of cognition, during many centuries the central site of emotion and thought was assigned to the heart. This belief was maintained along centuries despite the accumulation of evidence that pointed to the importance of the brain. Early notions on this can be found in texts written in what now is Iraq about 4000 years ago (see Figure 1.7), and in others in following cultures and world locations. The first written challenge to this heart-centered view was in ancient Greece (600-250 BCE), based on some rudimentary anatomy linked to the school of medicine where Hippocrates belonged to. However, the heart notion prevailed as self-evident, and was defended by many including Aristotle, who characterized the brain as a coolant system.
Despite the accumulation of evidence, it took 400 years since Aristotle to obtain decisive evidence of the role of the brain as support of the mind, through the work of Galen (born 129 CE in now Turkey) as anatomist studying the effect of injuries in the brain of gladiators. Galen conducted “lecture-commentaries” where he performed live experimentation on animals.
For example, to prove that the brain nerves were responsible of the production of voice, he tied a thread tightly around the laryngeal nerves of pigs and showed that the squealing of the animal ceased, and it returned when the ligature was loosened. Squeezing of the heart, on the other hand, did not prevent the generation of vocal sounds. On the basis of this and many other experiments, Galen was certain that the brain, and not the heart, was the core organ of thought. Despite all the evidence, the Aristotelian heart-centered explanation continued dominating the general opinion, whereas brain-based explanations placed the presence of animated spirits in the ventricles of the brain (which were created in the heart, and transported in the blood). In the XVIth century, the work of the famous Vesalius (father of modern anatomy) was based on the idea that the brain was the base of thought. In his book De Humani Corporis Fabrica, he drew ventricles in large detail but left the cortex underdefined and many times schematic. He, however, contended that the ventricles appeared to be “nothing more than cavities”. Interestingly, Vesalius noted that the extensive anatomical knowledge that he had gathered through dissection was not useful to explain how the body and brain actually worked, and that nothing could be told about the location of faculties in the brain. That is, Vesalius already noted that anatomy on its own cannot explain mental function.
1.2.3 From mechanical forces to electricity
Along the XVIIth century, the idea that the brain was the seat of the mind slowly settled among the majority, in part due to the work of René Descartes (published posthumously due to his fear of the Catholic church). He popularized a model of mechanic forces or machines to explain simple human behavior (reflexes), where fluid animal spirits (generated by the pineal gland) moved rapidly in the nerves. For a while, explanations of brain function relied on mechanic forces moving or vibrating the animal spirits or fluids along the nerves of the body. However, these analogies of humans and machines met furious opposition from authorities of religion, and many of them were prosecuted and banned even when printed in anonymity.
Electricity became a matter of public interest in the XVIIIth century, and it was soon realized that it could affect the body of any animal, including dead ones, and from here it was linked to previous explanations of vibrations of the animal spirit in humans. Luigi Galvani performed experiments conducting electrical currents on amputated limbs frogs and of other animals and showed that “animal electricity” was clearly manifested in the movement of the muscles. He also suggested that the mind affected the brain by this same electrical means. Later, his nephew Aldini performed experiments showing how currents induced with batteries generated coordinated movements in human cadavers, which provided stronger support for electricity as a source of complex behavior. He also used batteries to create pioneering electrical therapy on depressed patients. Years later (1850), Alfred Smee claimed that the brain was comprised of thousands of small electric batteries, and constructed theoretical neural networks with feedforward and recurrent connections among the batteries, and also applied this theory to the nature of human ideas and consciousness. The brain and bodies of humans and other animals worked by the same general principles, the difference being the number and organization of its electrical components.
1.2.4 Phrenology and mental function
Phrenology (“study of the mind”), initially known as cranioscopy, was a very popular doctrine in the XIXth century that claimed that it was possible to determine someone’s personality by measuring the bumps of the scalp. Franz Gall and later Johann Spurzheim conceived the idea that human behavior and personality could be divided into different innate mental faculties, which each resided on different organs or parts of the brain, and that by measuring the size of the skull covering these organs their importance for each person could be determined. This theory, which despite its popularity was never accepted by academia (or by the Catholic church, for that matter), provided three insights that still today inform our understanding of the link between the human mind, brain and behavior. First, phrenological explanations focused on the brain and not the heart, claiming that “the brain is the organ of all the sensations and of all voluntary movements”. Second, the discipline put forward the localization of mental function in specific regions of the brain. And third, Gall contended humans and other animals shared most of the psychological faculties (only 8 of their 27 faculties were unique to humans, including e.g. wisdom and poetry).
After years of growth, phrenology wane due to lack of evidence for its tenets. One of their contenders, Flourens, performed countless experiments removing different parts of the brain of different animals and concluded that “the cortex, the seat of intelligence, was a unitary structure”, and that localization only applied to very basic physiological functions such as breathing or motor coordination. This tension between localization of function and brain equipotentiality still holds nowadays.
1.2.5 Neuropsychology
In 1861, the French surgeon Paul Broca claimed that there was a clear association between brain size an intelligence, based on supposed differences between races and also between men and women. He also described the brain of a deceased man with severe lesions in the left frontal lobe, which had been unable to speak for decades (only repeating tan-tan) but had otherwise normal mental faculties. Broca assembled several cases of speech loss or aphasia, all of them linked to lesions on the same brain region. The implication was that one area of the brain served a circumscribed brain function, that is, that mental function could be localized, as phrenologists had also claimed. Soon after, Carl Wernicke reported the case of a woman who could speak but did not understand language, which suggested that other regions were specialized in language comprehension. A highly unethical direct demonstration of localization was performed soon after by the surgeon Robert Bartholow, who electrically stimulated different regions of the cortical surface of the brain of Mary Rafferty, a patient with partial skull damage due to a severe ulcer (and who died soon after these experiments took place). Stimulation resulted in different behavioral consequences depending on the region, supporting compartmentalization of function on the human cortex. Since its beginning, the effects of circumscribed brain lesions on human behavior and cognition have been a source of invaluable information to understand the relationship between brain and mind.
1.2.6 Behavioral Neuroscience
Converging evidence of cortical localization stem from the work of Fritsch and Hitzig, who employed delicate electrodes to stimulate with weak currents the cortex of anesthetized dogs and observed that different locations led to different movements. Ferrier complemented these experiments with interventions in monkeys that offered similar overall results. Apart from movement, he provided evidence supporting the localization of reflective faculties, such as attention. Up to this point, however, investigators had no model of how the brain worked, and many doubted about the ability of science to eventually understand the brain and higher human mental function, our how consciousness could emerge from brain matter.
In the XIXth century it was discovered that cells compose living organisms, and also the brain. Despite this large advancement, a major dispute took place regarding how these cells were organized in the brain. Although it was clear that in the body cells were discrete units bounded by membranes, Purkinje’s microscopic observations of the human cerebellum suggested that brain’s cells formed a single organic network. Thanks to the work of Ramón y Cajal employing the Golgi staining method, it was established that nerve cells were also independent units, which were labeled neurons. “The most subtly complicated machine to be found in all of nature” had found the units of its complex structural organization. Paired with the action potential (clarified by the work of Hodgkin and Huxley, 1939), these discoveries provided the units that could be manipulated and measured in response to external stimulation to study brain function, which is a crucial aspect for Cognitive Neuroscience.
Hubel & Wiesel (1959) measured the activity (action potentials) of neurons in the visual areas of cats while they were presented visual stimuli, and showed that neurons located in different regions responded to stimuli with different characteristics. With these innovative functional experiments, they were able to draw a map of visual selectivity in the occipital cortex. This line of work progressed with Allman & Kaas (1971) describing the topographical organization of the extrastriate cortex or Zeki describing the connections among visual areas and the selectivity of association areas such as V5. Years later, Newsome and colleagues (1989) showed how the information about motion represented by neurons in V5 affected decision-making of monkeys, pushing the study of high-level cognition to the single-cell level.
1.2.7 Mental chronometry and Cognitive Psychology
Science relies strongly on the ability to manipulate the object of study and to measure with precision what happens to this object in reaction to our manipulations. These are labeled as independent and dependent variables, respectively. Having the means to properly manipulate and to measure is as essential as having a clear definition of the object that we plan to manipulate and to measure. As we have seen in the previous section, the realization that mental function resides in the brain, and that neurons communicate information with electricity that can be measured in action potentials, defined a unit of measurement for the neural side of the story. In terms of the mind, however, the divisions put forward by phrenologists were anecdotal and lacked scientific rigor. How could cognition be manipulated and measured in humans?
Cognitive Psychology was sustained on the metaphor that human minds could be compared to computer software. Computers receive input, process the information according to a goal and generate an output. We could then give inputs to human (stimuli), study how they process the relevant information, and measure their reaction to this. In this information-processing framework , Milner (1978) proposed that mental complex operations such as perception, memory, language, attention, etc., could be divided into simpler ones, and these simpler processes could be studied separately. Along the years, several theoretical models have been build in Cognitive Psychology trying to explain how all these mental phenomena work, at the basic level, by designing tasks that tap into cognitive processes and measuring the response that humans give when confronted with them.
Many of these tasks rely on mental chronometry, a strategy put forward by Franciscus Donders (1869). Here, the speed of responses (Reaction Time, or RT) of humans in reaction to stimuli is measured and compared across different conditions of experimental presentations. Donders measured the time that it took people to (1) detect a simple visual stimulus, and compared this to the time needed to (2) recognize the same stimuli and to choose between two of them. These are called experimental conditions. By comparing the relative times between these conditions (employing the so-called subtraction methodology) he could infer the time that mental processes took. For example, the subtraction of the detection time from the discrimination time allows the calculation of how much time it takes to make a visual discrimination. Mental chronometry has been continuously refined over the years, and together with accuracy, it represents one of the main sources of information employed to study mental processes. These processes represent the unit of measurement of cognition.
Among the many scientists that have contributed to Cognitive Psychology, Michael Posner has been a key figure to translate mental chronometry applied to behavioral data (with RT) to the study of cognitive processes in the human brain. In 1994, together with Michael Raichle he published the book Images of Mind, where he laid out their initial efforts to use mental chronometry to localize cognitive processes in the human brain. The logic was the same as with mental chronometry, but adding neuroimaging methodology while the participants performed the task. The brain activity that appears differentially between the two experimental conditions manipulated can be associated with the cognitive process that they isolate. Returning to the initial experiment of Donders, with his subtraction method we could localize which brain regions are involved in choice or decision-making, which is a high-level element of human cognition.
1.2.8 Non-invasive neuroimaging
As stated above, the capacity to measure the object of study determines to a large extent the progress of its scientific understanding. Measuring the human brain is not an easy endeavor, and for many centuries its anatomy could only be ethically studied post-mortem. Also, knowledge about anatomy does not easily inform function. An essential ingredient in Cognitive Neuroscience are the recent methods that allow to measure the brain at work while participants are performing the tasks that have been developed in Cognitive Psychology for several decades, combining in a meaningful way brain and cognition.
The first recording method that could be employed non-invasively with humans was electroencephalography (EEG), described by Hans Berger in 1929 while he was trying to study the physiological basis of psychic events (telepathy). As EEG relies on electrical oscillations triggered by neurons, it has a very good temporal resolution that is well fitted to the fast speed of cognitive events. A few decades later magnetic resonance imaging (MRI) was developed thanks to the work of Lauterbur and Mansfield (1973). This method can be used to obtain images reflecting the anatomy or structure of the brain with fairly good resolution (e.g. current structural brain images have 1x1x1 mm or even higher). Crucially, soon after positron emission tomography (PET, 1979) and functional MRI (fMRI, Ogawa, 1990) were developed, offering unprecedented information of increased blood flow to areas engaged during specific cognitive processes. Also, Transcranial Magnetic Stimulation (TMS, 1985) started to being used to briefly disrupt the activity of targeted brain regions, allowing the measurement of the causal effect of virtual brain lesions on complex human behavior. Altogether, these neuroimaging methods bring powerful unprecedented tools to investigate the brain basis of the human mind, an endeavor that many had thought inaccessible to science.
1.2.9 Signal engineering for data analyses
Measuring brain activity non-invasively is essential for Cognitive Neuroscience, but being able to interpret the resulting data is also crucial. This is, however, not an easy task. The brain is a complex organ that receives loads of information from the senses, analyzes and transforms this information in many different ways depending on the task at hand, and generates an almost infinite repertoire of behavioral patterns. This happens at a very fast pace and through the interaction of many different brain areas. The data that reflects this is very complex and not interpretable straight away.
Hence, the growth of the discipline goes hand in hand with the development of analysis methods that help to interpret the neuroimaging signal into meaningful bits. Signal engineers and other professionals have developed a myriad of such analysis strategies, many of which are freely available to the academic community. Well-known packages include EEG lab of Fieldtrip for EEG data, and SPM or FSL for magnetic resonance. Along these pages we have seen how knowledge has evolved from the idea that mind and brain are qualitative different substances to being able to measure and study the human brain while it is generating purposeful complex behavior. Whereas these advances have been astonishing, there is still much more we do not know.
1.3 Opposing views of brain functioning
1.3.1 Localization vs. equipotentiality
One of the big questions when thinking about the relationship between mind and brain is the extent to which mental function can be localized in the brain, and we have seen examples of these two views along the historical foundations of the discipline. Far from being solved, nowadays there are scientist that pursue a highly localizationist strategy, trying to find the exact site of precise computations in the brain, whereas others lean towards non-localization and prefer to focus their analyses on highly interactive networks of brain areas. The fact is that there is evidence in support of both options, which could seem impossible at first glance. Localizing basic perceptual and motor functions, which rely on primary visual and motor regions, seems to be rather straightforward. In contrast, more complex cognitive functions, such as attention or memory, rely on many brain areas, including high-level associative brain regions, where localization is more diffuse.
Thus, it seems the extent of precise localization may depend on the specific operation under study: whereas basic mental functions seem to be processed in fairly modular and localized regions of the brain, high-level cognition seem to rely on the interaction of several areas that process and represent information in a highly abstract fashion. This difference could explain, at least in part, the seemingly different results obtained after lesions of brain regions in non-human animals and neuropsychological patients.
1.3.2 Task vs. rest: A default mode of brain function
Until recently, the study of human brain activity was dominated by the reminiscent computer analogy, where different stimuli were presented and participants were asked to perform multiple tasks on them. That is, brain activity was measured as a reaction to stimulation, which agreed with the view of the brain as a reactive organ. There were, however, several pieces of evidence that do not fit with this interpretation and point to the existence of intrinsic brain operations that are not task-related. The brain is also a reflexive organ, with a large proportion of intrinsic activity unrelated to task demands. First, although the brain represents only 2% of the total body weight, it consumes 20% of all body energy. Of all this energy, a large portion ( 60 - 80%) is related to glutamate cycling, that is, neural signaling. However, task performance only explains 5% of all this energy consumption, whereas the remaining is unexplained. That is, the majority of the brain’s energy consumption is devoted to neural signaling that is functionally relevant but is independent of the task that the person is doing: this is known as intrinsic brain activity.
Intrinsic activity is evident in neuroimaging recordings such as EEG, which shows oscillatory brain activity of different speeds that changes with time across the whole brain. For many years, however, it was assumed that most of this activity corresponded to noise , was treated as such and eliminated from the analyses as irrelevant.
Employing fMRI data, Bharat Biswal was the first researcher (then an engineer PhD student) to claim that the so-called noise was not such, but rather represented the activation of intrinsic brain networks, that is, regions of brain that were always activating in a coherent manner. This coherence is reflected in the correlation of activations between different regions: if one region increases its activation, so does the other, and in the same manner, both regions decrease their activity in a similar way. Analyzing the signals that came from the scanner, Biswal was able to show the existence of coordinated brain activity in sensorimotor regions of the two hemispheres, and also diverse regions linked to language or visual processing.
Marcus Raichle was also one of the pioneers in this field. He reported the first observation of the so-called Default-mode network (DMN), a network of brain areas (including regions of the medial prefrontal, posterior parietal and medial temporal cortices, and also the precuneus) that increase their activity when the person is at rest in the scanner (i.e., performing no task) and also shows coherent brain patterns of activation. Such coherent activations are also observed during anesthesia, sleep and in non-human animals, which speaks to the robustness of the phenomenon.
Further research has shown that the brain’s intrinsic activity contains signatures of many other networks apart from the DMN. These networks found at rest are strikingly similar to those involved during the execution of tasks of different nature. This strongly suggests that regions that tend to co-activate during task execution also connect when the brain is “at rest”, forming the brain’s functional backbone.
Changes in intrinsic network connectivity have been related to development, neurodegenerative diseases and also several psychiatric diseases, and the field is rapidly expanding with the goal of using activity in these networks as potential diagnostic tools to predict future mental dysfunction.
1.4 Core experimental questions in Cognitive Neuroscience
The field of Cognitive Neuroscience gathers professionals from multiple disciplines, including experimental and clinical psychologists, neuroscientists, signal and computer engineers and physics, and this variety of professionals usually lead to research programs focused on different research questions. Many of these, however, can be grouped in a few core families of experimental questions.
1.4.1 Characterization of Cognitive Functions
Sometimes researchers use neuroimaging tools to advance the knowledge about psychological processes or theories per se, and the information gained about the brain is secondary to this. That is, they use neuroimaging technologies to measure brain activity during the performance of their processes of interest and use their result to draw inferences about how cognition works. An example could be of an investigator who wants to study if verbal language perception also involves motor representations. The activation of brain motor regions during a purely perceptual task would provide support for this hypothesis, whereas the lack of it would not.
1.4.2 Localization of cognitive processes
Experiments where the main goal is to learn where in the brain a cognitive process lies are also frequent. Here the researcher uses cognitive tasks and usually subtraction inferences to investigate which areas increase their activation during one condition compared to another control condition. This endeavor requires neuroimaging methods with good spatial resolution, such as the fMRI. In a classic example, Posner and Petersen (1989) localized the regions involved in different stages of language processing (viewing words, reading them aloud, generating verbs reflecting their potential use, e.g. hammer – pound) by subtracting the average brain activity between them. They showed that visual word perception engaged the occipital and ventral temporal cortex, reading them aloud engaged motor areas, and left inferior frontal regions supported verb generation.
1.4.3 Computations and representation of information
In addition to knowing that an area is involved in a certain mental function (e.g. ventral temporal cortex in visual perception), a further question is to learn how neurons represent the information, that is, what is the neural code for this. For example, researchers investigate how neurons represent specific objects or their categories: is it that one neuron responds only to a certain stimuli, or the same neuron responds to several different objects with varying strength? Another line of research aims to discover which are the basic dimensions (e.g. stimulus orientation, brightness, complexity, animacy…) that guide how the information is coded in the brain.
1.4.4 Networks: Communication of information between brain areas
It is well known that many cognitive functions take place through the interaction of populations of neurons located in different parts of the brain. This means that neurons in a certain region process information and the result is passed on to other regions, and so forth. The set of brain regions and connections between them that work together to generate mental functions are called large-scale brain networks. The properties of these networks as a whole can be studied using models from the mathematical discipline of Complex Systems, which characterizes their properties in terms of how efficient they are, the level of modularity in their function, and many other factors. Functional networks are studied both when the person is performing tasks and also when they are “at rest”. An important addition to these are structural networks, that provide information regarding the white matter fibers that anatomically connect the different brain areas, and that constrain the scope of their functional interactions.
1.4.5 Individual differences
Humans differ in many different psychological characteristics and mental abilities, such as extraversion, intelligence or meditation skills. Brains can also be compared in terms of development, and mental disorders such as schizophrenia. Neuroimaging data can be used to compare groups of individual differing in these characteristics, with the goal of studying the underlying functional and structural brain differences that correlate with the differences of interest. These results in turn can aid to better understand these phenomena both at cognitive and neural levels.
1.5 Applications
Cognitive Neuroscience is rapidly increasing our knowledge about how the brain supports cognition. As explained above, this increases knowledge about the brain, but also of the cognitive processes investigated or other domains related to psychology, such as education. But in addition, this knowledge is being applied to diverse fields, including the following:
Discovery of early biomarkers of developmental, mental or other neurological diseases: There is a large interest in finding markers or indices in the profile of brain activations and/or structure that can be used to detect these problems as early as possible, to aid in their diagnosis and also to suggest potential targets for intervention. Although this field is of high interest to society due to the large benefits it may bring, there is still much to learn to be able to obtain biomarkers that are reliable at the individual level, due to current limitations in the methods and analyses available.
Intervention of disorders through neurofeedback: The technique of neurofeeback allows humans to learn to control certain aspects of their brain function. Through neurofeedback (usually implemented using EEG or fMRI), participants receive online information about a certain index of brain activity of interest and receive online feedback about their progress in modulating such index. In a slow trial-and-error process, a large proportion of participants become able to alter these indices, although the underlying mechanisms of this learning are not fully clear. In addition, currently there is little consensus on which brain markers should be used as targets for neurofeedback in different disorders (as the underlying biological causes of these disorders are not fully clear).
Generation of effective brain-computer interfaces (BCI): The field of BCI has a large history in Neuroscience, with the goal of building mechanisms to aid people with disabilities to communicate, regain control of their limbs or ameliorate symptoms of diseases (e.g. like deep neural stimulation in Parkinson patients). More recently, there are attempts to build BCI with more advanced capacities, such as using a brain interface to type directly into the phone. However, most of these are far from having a solution to all the inherent difficulties associated with this goal.
1.6 Neuro-hype
Overall, there is tendency to think that research about the brain more “scientific” or solid than research about the human mind, but this is only a delusion generated by mental biases. Several experiments have shown that presenting colorful brain pictures next to the same set of assertions increases the ratings of the readers on credibility and appeal of the contents. The increased allure of brain images also seems to extend to related words, such as “neuro”. Unfortunately, this has led to the emergence of pseudo-scientific fields where the word “neuro” is attached to many words without adding actual meaning to the original, in an intent of making it more appealing to the public. Among many others we can find neurocoaching, neuropsychoanalysis, neuroleadership, neuromeditation, neurodrinks or neurogum.
Although the scientific advances in the field of Cognitive Neuroscience are enormous, unfortunately it is also quite common to find areas that oversell the results to the lay public, and generate misinformation and erroneous interpretations. This is also often made worse by press releases looking for click baits. For a non-specialized audience, it is difficult to spot oversold claims about the potential implications of neuroscientific findings. As we will see along the course, there are many things we still do not know about how the brain actually works. In the same way as psychologists cannot “read minds”, neuroimaging cannot “see brains”. We should be cautious and wary of assertions that claim e.g. to know what is wrong with the brain of schizophrenics or the definite solution to deficits of attention with neurofeedback.